/*
 * Copyright 2016 The BigDL Authors.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
package com.intel.analytics.bigdl.dllib.nn.mkldnn

import com.intel.analytics.bigdl.dllib.nn.abstractnn.{Activity, AbstractModule}
import com.intel.analytics.bigdl.dllib.tensor.TensorNumericMath.TensorNumeric

import scala.reflect.ClassTag

/**
 * Identity just return the input to output.
 * It's useful in same parallel container to get an origin input.
 */
class Identity() extends MklDnnLayer {

  override def updateOutput(input: Activity): Activity = {
    output = input
    output
  }

  override def updateGradInput(input: Activity, gradOutput: Activity): Activity = {

    gradInput = gradOutput
    gradInput
  }

  override private[mkldnn] def initFwdPrimitives(inputs: Array[MemoryData], phase: Phase) = {
    _inputFormats = inputs
    _outputFormats = inputs
    (inputs, inputs)
  }

  override private[mkldnn] def initBwdPrimitives(grad: Array[MemoryData], phase: Phase) = {
    _gradOutputFormats = grad
    _gradOutputFormatsForWeight = grad
    _gradInputFormats = grad
    (grad, grad)
  }
}

object Identity {
  def apply[@specialized(Float, Double) T: ClassTag]()
    (implicit ev: TensorNumeric[T]) : Identity = {
    new Identity()
  }
}

